KR20200118525A - Evaluation of Parkinson's disease index using acceleration and angular velocity signals and method for evaluation thereof - Google Patents

Abstract

The present invention relates to a device and method for evaluating diagnosis of bradykinesia of the Parkinsonism using acceleration and angular velocity signals. More specifically, the present invention relates to the device and method for collecting data by analyzing acceleration and angular velocity signals in a time domain and a frequency domain using an IMU sensor and enabling systematic rehabilitation monitoring by quantifying the severity of the Parkinsonism with an objectified figure through the data.

Description

{Evaluation of Parkinson's disease index using acceleration and angular velocity signals and method for evaluation thereof}

The present invention relates to an apparatus for diagnosing and evaluating Parkinson's disease using acceleration and angular velocity signals, and an evaluation method using the same, and more specifically, by analyzing acceleration and angular velocity signals in time domain and frequency domain using an IMU sensor to collect data, The present invention relates to an apparatus for diagnosing and evaluating Parkinson's disease using the acceleration and angular velocity signals that enable the initial diagnosis by quantifying the severity of Parkinson's disease in an objective numerical value through the data and to enable systematic rehabilitation monitoring, and an evaluation method using the same.

Parkinson's disease is one of the representative neurodegenerative diseases caused by the loss of dopamine neurons. Neurodegenerative disease refers to a disease that causes abnormal brain function due to the destruction of nerve cells by some reason. Representative neurodegenerative diseases include Alzheimer's disease, Parkinson's disease, and rarely Lou Gehrig's disease.

Parkinson's disease is a disease that occurs mainly in older people, and the risk of contracting it increases with age. The incidence is known to be about 1 to 2 people per 1,000 population, and it is reported that about 1% of the elderly over 60 years old and about 2% of those over 65 suffer from Parkinson's disease.

The main symptoms of Parkinson's disease are movement disorders such as slow motion (slow movement), tremors at rest, and muscle stiffness. If Parkinson's disease is not treated appropriately, movement disorders gradually progress, making it difficult to walk and unable to perform daily life at all.

The most common symptom of Parkinson's disease, bradykinesia, refers to a state of slow movement. In addition to slowing down steps and hand movements, speech slows down, facial expressions disappear, and daily life such as washing face, makeup, bathing, eating, and wearing clothes It slows down several operations. Parkinson's disease often begins on either the left or the right side, so patients are often observed to shake one arm less while walking. Resting tremor appears as regular tremors in the arm being relieved. In the early days, you may not be aware of the shaking of your hand.

In examining Parkinson's disease, a clinical scale evaluation method in which a doctor sees and evaluates a patient's motion has been generally used. However, since such examination method is performed by subjective evaluation of doctors, there is a problem that objectivity decreases and subtle changes due to differences in individual evaluators and skill levels are not reflected.

Technologies for overcoming these problems and securing objectivity of evaluation have been developed, and an evaluation apparatus for Parkinson's disease has been disclosed. However, the evaluation device is not suitable for initial diagnosis because it detects continuous biometric information for a considerable period of time to evaluate the severity or state change of Parkinson's disease.

Therefore, in order to compensate for the above-described problems, the present inventors recognized that it is urgent to develop a diagnosis and evaluation device for Parkinson's disease that can be initially diagnosed by quantifying the severity of Parkinson's disease with objective values, and thus completed the present invention.

Japanese Patent Publication No. 2009-291379

An object of the present invention is to collect data by analyzing acceleration and angular velocity signals in the time domain and frequency domain using an IMU sensor, and quantify the severity of Parkinson's disease as an objective number through the data to enable initial diagnosis and systematically It is to provide an apparatus for diagnosing and evaluating Parkinson's disease using acceleration and angular velocity signals that enable rehabilitation monitoring.

Another object of the present invention is to provide a method for diagnosing and evaluating Parkinson's disease using the acceleration and angular velocity signals.

In order to achieve the above object, the present invention provides a Parkinson's disease dysphoria diagnosis and evaluation apparatus capable of initial diagnosis by quantifying the severity of Parkinson's dysphoria in an objective numerical value, and an evaluation method using the same.

Hereinafter, the present specification will be described in more detail.

The present invention includes an IMU sensor unit for outputting acceleration and angular velocity signals according to movement of a subject's thumb and index finger, converting the signal into a time domain and a frequency domain, and transmitting data to an external device; An index extraction unit for estimating movement angles of the thumb and index finger of the subject using the signal transmitted by the IMU sensor unit, and extracting a diagnosis index for Parkinson's disease using the estimated angle; And a calculation unit for extracting the severity of Parkinson's disease dysphoria as a quantified diagnosis score using the diagnostic index.

In the present invention, the IMU sensor unit includes an acceleration sensor unit for outputting an acceleration signal according to the movement of the subject's hand; An angular velocity sensor unit for outputting an angular velocity signal according to the subject's hand movement; And a communication unit that converts the signals output by the acceleration sensor unit and the angular velocity sensor unit into a wireless communication signal and transmits the wireless communication signal to an external device.

In the present invention, the diagnostic index includes an angle diagnosis index consisting of an angle of movement of the thumb and index finger of the subject, a coefficient of variation of the angle, and a reduction rate of the angle; A movement diagnosis index comprising a movement period of the thumb and index finger of the subject, a coefficient of variation of the movement period, and an increase rate of the movement period; And a magnitude of the angular velocity and acceleration of the time domain converted into the time domain. And an original signal diagnosis index comprising a median frequency converted into the frequency domain.

In addition, the present invention provides a method for diagnosing and evaluating Parkinson's disease, which includes the following steps.

(S1) outputting acceleration and angular velocity signals according to movements of a subject's thumb and index finger by an IMU sensor unit, converting the data into a time domain and a frequency domain, and transmitting the data to an external device;

(S2) The motion angle of the subject's thumb and index finger is applied to the transmitted data by applying a low pass filter of 4 Hz to estimate a motion angle, and an index extraction unit uses the estimated motion angle. Extracting a diagnostic index for Parkinson's disease dysphoria; And

(S3) The diagnostic index is a step of diagnosing Parkinson's disease by extracting the severity of Parkinson's disease as a quantified diagnosis score through a calculation unit.

In the present invention, the diagnostic index extracted in the step (S2) includes an angle diagnosis index consisting of an angle of movement of the thumb and index finger of the subject, a coefficient of variation of the angle of movement, and a rate of decrease of the angle; A movement diagnosis index comprising a movement period of the thumb and index finger of the subject, a coefficient of variation of the movement period, and an increase rate of the movement period; And a magnitude of the angular velocity and acceleration of the time domain converted into the time domain. And an original signal diagnosis index comprising a median frequency converted into the frequency domain.

In the present invention, the diagnostic score quantified the severity of Parkinson's disease extracted in the step (S3) is characterized in that it is extracted through the following [Equation 1].

[Equation 1]

Deg. : Motion angle of the subject's thumb and index finger

Freg. : Subject's thumb and index finger movement cycle

CoV(Angle): Coefficient of variation of angle

CoV(Freq.): Coefficient of variation of motion period

Amp. : Size of angular velocity in time domain converted to time domain

In the present invention, the diagnosis of Parkinson's disease in (S3) is characterized in that it is performed by the diagnostic score of the following [Table 1].

[Table 1]

All matters mentioned in the above devices and methods apply equally unless contradictory to each other.

The apparatus for diagnosing and evaluating Parkinson's disease dysphoria of the present invention uses an IMU sensor to analyze acceleration and angular velocity signals in the time domain and frequency domain to collect data, and objectify the severity of Parkinson's disease dystrophy through the data. By quantifying numerically, initial diagnosis is possible and systematic rehabilitation monitoring is possible.

1 is a block diagram schematically showing an apparatus for diagnosing and evaluating Parkinson's disease, according to a preferred embodiment of the present invention.
2 is a block diagram schematically showing a method for diagnosing and evaluating Parkinson's disease, according to a preferred embodiment of the present invention.
3 is a photograph of performing a movement for diagnosing Parkinson's disease dysphoria by wearing the apparatus for evaluating Parkinson's disease dysphoria according to a preferred embodiment of the present invention.
Figure 4 shows that the impact point in the acceleration and angular velocity signals is estimated by applying a low pass filter 4 Hz to the data transmitted in step (S1) of the method for diagnosing Parkinson's disease of the present invention. It is a graph.
5 shows (A) a motion angle of the subject's thumb and index finger, and the magnitude of the angular velocity and acceleration in the time domain converted into the time domain; And (B) a coefficient of variation of the angle, a rate of decrease of the angle, a movement period of the thumb and index finger of the subject, a coefficient of variation of the movement period, and A graph showing the diagnostic index value of the increase rate of the movement period.
6 is a graph showing a result of diagnosing a patient with Parkinson's disease dysphoria using the apparatus for diagnosing Parkinson's dysphagia according to a preferred embodiment of the present invention.

The terms used in the present specification will be briefly described, and the present invention will be described in detail.

The terms used in the present invention have been selected from general terms that are currently widely used while considering functions in the present invention, but this may vary depending on the intention or precedent of a technician working in the field, the emergence of new technologies, and the like. Therefore, the terms used in the present invention should be defined based on the meaning of the term and the overall contents of the present invention, not a simple name of the term.

When a part of the specification is said to "include" a certain element, it means that other elements may be further included rather than excluding other elements unless specifically stated to the contrary.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those of ordinary skill in the art may easily implement the present invention. However, the present invention may be implemented in various different forms and is not limited to the embodiments described herein.

Specific matters, including the problems to be solved, means for solving the problems, and effects of the present invention, are included in the following examples and drawings. Advantages and features of the present invention, and a method of achieving them will become apparent with reference to the embodiments described below in detail together with the accompanying drawings.

Hereinafter, the present invention will be described in more detail with reference to the accompanying drawings.

Parkinson's disease dysphoria diagnosis and evaluation device

1 is a block diagram schematically showing an apparatus for diagnosing and evaluating Parkinson's disease, according to a preferred embodiment of the present invention.

Referring to FIG. 1, the present invention includes an IMU sensor unit 100 that outputs acceleration and angular velocity signals according to movements of a subject's thumb and index finger, converts the signal into a time domain and a frequency domain, and transmits the data to an external device; Index extraction unit 200 for estimating the movement angle of the subject's thumb and index finger using the signal transmitted by the IMU sensor unit 100, and extracting a Parkinson's disease diagnosis index value using the estimated angle ; And a calculation unit 300 for extracting the severity of Parkinson's disease dysphoria as a quantified diagnosis score using the diagnostic index.

The IMU sensor unit 100 includes an acceleration sensor unit 110 for outputting an acceleration signal according to the movement of the subject's hand; An angular velocity sensor unit 120 for outputting an angular velocity signal according to the movement of the subject's hand; And a communication unit 130 that converts signals output by the acceleration sensor unit 110 and the angular velocity sensor unit 120 into a wireless communication signal and transmits the wireless communication signal to an external device.

The IMU sensor unit 100 may be manufactured in the form of an adhesive patch, band, or thimble attached to the thumb and index finger of the subject, and is attached to the thumb and index finger of the subject and randomly from the thumb and index finger of the subject ( random) is not limited thereto.

The acceleration sensor unit 110 and the angular velocity sensor unit 120 may output acceleration and angular velocity signals according to movements of the subject's thumb and index finger, and convert the signals into time domain and frequency domain. In particular, when converting the signals output by the acceleration sensor unit 110 and the angular velocity sensor unit 120 into the frequency domain, it may be performed by Fourier transform or wavelet transform. This can be done by Fourier transform.

The Fourier transform is an algorithm that calculates an approximate value of a function and refers to a mathematical transformation method in which a signal is decomposed into a component of a frequency.

The wavelet transformation refers to a transformation method for representing time and frequency components for a signal whose frequency components change over time.

The acceleration sensor unit 110 and the angular velocity sensor unit 120 may convert the acceleration and angular velocity signals into the acceleration and angular velocity data in the time domain and the frequency domain, and the acceleration and angular velocity may be the root mean square velocity ( It can be expressed as a vector value of root-mean square velocity (rms) or a median frequency value.

The “root mean square velocity” means a value obtained by averaging the squares of the velocity magnitudes of particles.

The communication unit 130 may convert signals output by the acceleration sensor unit 110 and the angular velocity sensor unit 120 into a wireless communication signal, and transmit the wireless communication signal to an external device.

The wireless communication signal may be Radio Frequency (RFID), Near Field Communication (NFC), Magnetic Secure Transmission (MST), Bluetooth, WiFi, or Near Field Magnetic Induction (NFMI).

The external device may be a computer, a notebook computer, a mobile or a tablet PC, but a display capable of visualizing and confirming signals output by the acceleration sensor unit 110 and the angular velocity sensor unit 120 is provided. If it is a device, it is not limited thereto.

In the present invention, the index extraction unit 200 estimates the movement angle of the thumb and index finger of the subject using the signal transmitted by the IMU sensor unit 100, and Parkinson's disease using the estimated angle. It is possible to extract the value of the diagnosis index for dysphoria.

More specifically, the index extraction unit 200 may estimate the motion angle of the thumb and index finger of the subject using the acceleration and angular velocity signals extracted by the acceleration sensor unit 110 and the angular velocity sensor unit 120. have. In addition, the index extraction unit 200 may extract a diagnosis index for Parkinson's disease dysphoria using the estimated motion angle.

The diagnostic index includes an angle diagnosis index consisting of an angle of movement of the subject's thumb and index finger, a coefficient of variation of the angle, and a reduction rate of the angle; A movement diagnosis index comprising a movement period of the thumb and index finger of the subject, a coefficient of variation of the movement period, and an increase rate of the movement period; And a magnitude of the angular velocity and acceleration of the time domain converted into the time domain. And an original signal diagnostic index comprising a median frequency converted into the frequency domain.

In the present invention, the calculation unit 300 may extract the severity of Parkinson's disease dysphoria as a quantified diagnosis score using the diagnostic index extracted by the index extraction unit 200. More specifically, the calculation unit 300 may extract the severity of Parkinson's disease as a diagnostic score through the following [Equation 1].

[Equation 1]

Deg. : Motion angle of the subject's thumb and index finger

Freg. : Subject's thumb and index finger movement cycle

CoV(Angle): Coefficient of variation of angle

CoV(Freq.): Coefficient of variation of motion period

Amp. : Size of angular velocity in time domain converted to time domain

Parkinson's disease dysphoria diagnosis and evaluation method

3 is a block diagram schematically showing a method for diagnosing and evaluating Parkinson's disease, according to a preferred embodiment of the present invention.

The present invention provides a method for diagnosing Parkinson's disease dysphoria comprising the following steps.

(S1) outputting acceleration and angular velocity signals according to the movement of the subject's thumb and forefinger by the IMU sensor unit 100, converting the data into the time domain and the frequency domain, and transmitting the data to an external device;

(S2) The motion angle of the subject's thumb and forefinger is applied to the transmitted data by applying a low pass filter of 4 Hz to estimate a motion angle, and an index extractor 200 using the estimated motion angle. ) Extracting a diagnostic index value for Parkinson's disease; And

(S3) Diagnosing Parkinson's disease by extracting the severity of Parkinson's disease as a quantified diagnosis score through the calculation unit 300 using the diagnostic index.

In the present invention, the step (S1) outputs acceleration and angular velocity signals according to the movement of the subject's thumb and forefinger by the IMU sensor unit 100, and converts the signal into the time domain and the frequency domain to convert the external device. Transfer to; is.

More specifically, in step (S1), the IMU sensor unit 100 is attached to the subject's thumb and index finger, and an acceleration and angular velocity signal according to the movement of the subject's thumb and index finger are output. In addition, the output acceleration and angular velocity signals are converted into wireless communication signals through a communication unit, and the wireless communication signals are digitized and transmitted to an external device.

The IMU sensor unit 100 may be manufactured in the form of an adhesive patch, band, or thimble attached to the thumb and index finger of the subject, and is attached to the thumb and index finger of the subject and randomly from the thumb and index finger of the subject ( random) is not limited thereto.

The acceleration sensor unit 110 and the angular velocity sensor unit 120 may output acceleration and angular velocity signals according to movements of the subject's thumb and index finger, and convert the signals into time domain and frequency domain. In particular, when converting the signals output by the acceleration sensor unit 110 and the angular velocity sensor unit 120 into the frequency domain, it may be performed by Fourier transform or wavelet transform. The acceleration sensor unit 110 and the angular velocity sensor unit 120 may convert the acceleration and angular velocity signals into the magnitude of the acceleration and angular velocity in the time domain and the frequency domain, and may be performed by Fourier transform. The acceleration and angular velocity may be expressed as a vector value of a root-mean square velocity (rms) or a median frequency value.

The communication unit 130 may convert signals output by the acceleration sensor unit 110 and the angular velocity sensor unit 120 into a wireless communication signal, and transmit the wireless communication signal to an external device.

The wireless communication signal may be Radio Frequency (RFID), Near Field Communication (NFC), Magnetic Secure Transmission (MST), Bluetooth, WiFi, or Near Field Magnetic Induction (NFMI).

The external device may be a computer, a notebook computer, a mobile or a tablet PC, but a display capable of visualizing and confirming signals output by the acceleration sensor unit 110 and the angular velocity sensor unit 120 is provided. If it is a device, it is not limited thereto.

In the present invention, in the step (S2), the motion angle of the subject's thumb and index finger is applied to the data transmitted in the step (S1) by applying a low pass filter of 4 Hz to estimate the motion angle, Extracting a diagnostic index value for Parkinson's disease by the index extraction unit 200 using the estimated motion angle.

The diagnostic index includes an angle diagnosis index consisting of an angle of movement of the subject's thumb and index finger, a coefficient of variation of the angle, and a reduction rate of the angle; A movement diagnosis index comprising a movement period of the thumb and index finger of the subject, a coefficient of variation of the movement period, and an increase rate of the movement period; And a magnitude of the angular velocity and acceleration of the time domain converted into the time domain. And an original signal diagnostic index comprising a median frequency converted into the frequency domain.

First, in step (S2), the motion angle may be estimated by applying a low pass filter of 4 Hz to the motion angle of the subject's thumb and index finger to the data transmitted in step (S1).

Referring to FIG. 4, the data transmitted in the step (S1) applies a low pass filter of 4 Hz to find an impact point in the acceleration and angular velocity signals. The value at the impact point is reset to "0" to estimate the motion angle of the acceleration and angular velocity.

In this case, the impact point means a point at which a repetitive operation starts newly.

Next, in the step (S2), the diagnostic index for Parkinson's disease dysphoria may be extracted by the index extraction unit 200 using the estimated movement angle.

Referring to FIG. 5A, the angle of movement of the thumb and index finger of the subject in the diagnostic index, the magnitude of the angular velocity and acceleration of the time domain converted into the time domain; And, in the case of the median frequency converted into the frequency domain, the control group (normal person) is extracted with a higher value than the experimental group (Parkinson's disease patient). Further, referring to FIG. 5B, in the case of the coefficient of variation of the angle, the rate of decrease of the angle, the period of movement of the thumb and index finger of the subject, the coefficient of variation of the movement period, and the rate of increase of the movement period in the diagnostic index, a control group (normal person ) Is extracted with a significantly lower value than the experimental group (Parkinson's disease patients)

In the present invention, in the step (S3), the diagnostic index extracted by the indicator extraction unit 200 in the step (S2) is extracted by the calculation unit 300 to extract the severity of Parkinson's disease as a quantified diagnosis score. Diagnosing dysphagia; is.

More specifically, the (S3) step is the final Parkinson's disease through the following [Equation 1] by combining the diagnostic index extracted by the index extraction unit 200 in the step (S2) with a specific normalizing factor. A diagnostic score that quantifies the severity of can be extracted.

[Equation 1]

Deg. : Motion angle of the subject's thumb and index finger

Freg. : Subject's thumb and index finger movement cycle

CoV(Angle): Coefficient of variation of angle

CoV(Freq.): Coefficient of variation of motion period

Amp. : Size of angular velocity in time domain converted to time domain

In the above [Equation 1], the specific normalizing factor is 180 for Deg., 2 for Freg., 100 for CoV(Angle), 100 for CoV(Freq.), 500×π for Amp. /180 and 2000.

In the specific normalization factor, Deg. was based on the maximum angle of 180°, and Freg. was based on the maximum period of 2 seconds (sec) set by the test. In addition, the specific normal conversion factor CoV (Angle) was in accordance with a percentage, and CoV (Freq.) was converted into a rad value based on the maximum angular velocity range of 500 deg/sec, and Amp. It was used as the specific normalized factor based on the maximum acceleration range of 2000 mg.

Hereinafter, the present invention will be described in more detail through the following examples and experimental examples. However, the following Examples and Experimental Examples are for illustrating the present invention, and the scope of the present invention is not limited by these Examples and Experimental Examples.

Example 1. Diagnosis of Parkinson's Disease

1. Select target

A total of 26 subjects, consisting of 16 experimental groups (suspected Parkinson's patients with suspicious Parkinson's disease) and 10 control subjects (normal subjects), were used as final subjects.

2. Experiment method

The present invention was worn (attached) to the thumb and index finger of 26 subjects, and the thumb and index finger were repeatedly diagnosed for 15 seconds at the maximum possible speed and angle. Quantified diagnostic scores for severity were extracted. The results are shown in the following [Table 2] and Fig. 6.

3. Test result

[Table 2]

As can be seen in [Table 2] and FIG. 6, in the case of the control group (normal person), it can be confirmed that the quantified diagnostic score for the severity of Kinson's disease dysphoria was 80 or more. On the other hand, in the case of the experimental group (a suspected Parkinson's disease patient), it can be confirmed that all 16 patients received a diagnosis score of 80 or less.

From the above results, it can be seen that the apparatus for diagnosing and evaluating Parkinson's disease of the present invention and a diagnostic evaluation method using the same can provide an initial diagnosis of a patient with Parkinson's disease and show remarkably high diagnostic accuracy.

From the above description, it will be understood that those skilled in the art belonging to the present invention can be implemented in other specific forms without changing the technical spirit or essential features of the present invention. In this regard, the embodiments described above are illustrative in all respects, and should be understood as non-limiting.

Parkinson's disease dysphoria diagnosis and evaluation device: 1
IMU sensor unit: 100
Angular velocity sensor unit: 110
Acceleration sensor unit: 120
Communication Department: 130
Indicator extraction unit: 200
Calculation: 300

Claims (7)

An IMU sensor unit that outputs acceleration and angular velocity signals according to the movement of the subject's thumb and index finger, converts the signal into a time domain and a frequency domain, and transmits the data to an external device;
An index extraction unit for estimating movement angles of the thumb and index finger of the subject using the signal transmitted by the IMU sensor unit, and extracting a diagnosis index for Parkinson's disease using the estimated angle; And
Parkinson's disease diagnosis and evaluation apparatus comprising a; calculating unit for extracting the severity of Parkinson's disease seodongjeung as a quantified diagnostic score using the diagnostic index. The method of claim 1,
The IMU sensor unit,
The IMU sensor unit may include an acceleration sensor unit for outputting an acceleration signal according to the movement of the subject's hand;
An angular velocity sensor unit for outputting an angular velocity signal according to the subject's hand movement; And
And a communication unit configured to convert the signals outputted by the acceleration sensor unit and the angular velocity sensor unit into a wireless communication signal and transmit the wireless communication signal to an external device. The method of claim 1,
The diagnostic index,
An angle diagnosis index consisting of an angle of movement of the subject's thumb and index finger, a coefficient of variation of the angle, and a reduction rate of the angle;
A movement diagnosis index comprising a movement period of the thumb and index finger of the subject, a coefficient of variation of the movement period, and an increase rate of the movement period; And
The magnitude of the angular velocity and acceleration of the time domain converted into the time domain; And an original signal diagnosis index consisting of a median frequency converted into the frequency domain. (S1) outputting acceleration and angular velocity signals according to movements of a subject's thumb and index finger by an IMU sensor unit, converting the data into a time domain and a frequency domain, and transmitting the data to an external device;
(S2) The motion angle of the subject's thumb and index finger is applied to the transmitted data by applying a low pass filter of 4 Hz to estimate a motion angle, and an index extraction unit uses the estimated motion angle. Extracting a diagnostic index for Parkinson's disease dysphoria;
(S3) The diagnostic index includes a step of diagnosing Parkinson's disease dysphoria by extracting the severity of Parkinson's disease as a quantified diagnostic score through a calculation unit. The method of claim 4,
The diagnostic index extracted in step (S2),
An angle diagnosis index consisting of an angle of movement of the subject's thumb and index finger, a coefficient of variation of the angle, and a reduction rate of the angle;
A movement diagnosis index comprising a movement period of the thumb and index finger of the subject, a coefficient of variation of the movement period, and an increase rate of the movement period; And
The magnitude of the angular velocity and acceleration of the time domain converted into the time domain; And an original signal diagnostic index consisting of a median frequency converted into the frequency domain. The method of claim 4,
The diagnostic score for quantifying the severity of Parkinson's disease extracted in the step (S3) is extracted through the following [Equation 1].
[Equation 1]

Deg. : Motion angle of the subject's thumb and index finger
Freg. : Subject's thumb and index finger movement cycle
CoV(Angle): Coefficient of variation of angle
CoV(Freq.): Coefficient of variation of motion period
Amp. : Size of angular velocity in time domain converted to time domain The method of claim 4,
In (S3), the diagnosis of Parkinson's dysphagia is performed by the diagnostic score of the following [Table 1].
[Table 1]

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